Inception neural network input layer confusion
The padding is not size zero* in the inception CNN layers. In fact it is deliberately chosen to pad so that the convolution by itself would produce an image the same size as the original. I.e. $p=(f−1)/2$, in some libraries this is called "same" padding.

So, $p=3$

The stride is not 2. It is $s=1$ for the convolution. The Inception CNN does not use strided convolutions. Instead the stride of 2 is associated with a later max-pooling layer.

Therefore, using $(((n+2p-f)/s)+1)$ with the correct values $(((224 + 6 - 7)/1)+1 = 224$

Then apply max-pooling, with stride 2. $224/2 = 112$.



* Not to be confused with "zero padding" which means pad using $0$ as the value to insert into the new area. So you can have "zero padding with $p=3$"